• Title/Summary/Keyword: Predictive indicators

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An Exploratory Study on the Prediction of Business Survey Index Using Data Mining (기업경기실사지수 예측에 대한 탐색적 연구: 데이터 마이닝을 이용하여)

  • Kyungbo Park;Mi Ryang Kim
    • Journal of Information Technology Services
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    • v.22 no.4
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    • pp.123-140
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    • 2023
  • In recent times, the global economy has been subject to increasing volatility, which has made it considerably more difficult to accurately predict economic indicators compared to previous periods. In response to this challenge, the present study conducts an exploratory investigation that aims to predict the Business Survey Index (BSI) by leveraging data mining techniques on both structured and unstructured data sources. For the structured data, we have collected information regarding foreign, domestic, and industrial conditions, while the unstructured data consists of content extracted from newspaper articles. By employing an extensive set of 44 distinct data mining techniques, our research strives to enhance the BSI prediction accuracy and provide valuable insights. The results of our analysis demonstrate that the highest predictive power was attained when using data exclusively from the t-1 period. Interestingly, this suggests that previous timeframes play a vital role in forecasting the BSI effectively. The findings of this study hold significant implications for economic decision-makers, as they will not only facilitate better-informed decisions but also serve as a robust foundation for predicting a wide range of other economic indicators. By improving the prediction of crucial economic metrics, this study ultimately aims to contribute to the overall efficacy of economic policy-making and decision processes.

Three Predictive Tests Using Mice for the Identification of Contact Sensitizer

  • Jung-Hyun Shin;Min
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.22 no.2
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    • pp.201-210
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    • 1996
  • Predictive tests for the identification of contact sensitizing chemicals have been developed. We measured the sensitization potential with three predictive tests, the in vitro and the in vivo Local Lymph Node Assay(LLNA), ELISA to detect interferon-gamma(IFN-${\gamma}$) from supernatant and flow cytometry to detect change of cell surface proteins, using draining lymph nodes of mice. BALB/c mice were exposed to various chemicals or vehicles on the ears daily for 3 consecutive days in all experiments. With some exceptions of propyl paraben, neomycin sulfate, the in vivo LLNA was able to detect the sensitizing capacity of test chemicals and was more sensitive than the in vitro LLNA for chemicals used in the present study. In another experiment, contact sensitivity was assessed by the ELISA to detect IFN-Υ from the supernatants of the cultured LNCs after sensitization with chemicals. There was a good correlation between the LLNA and the IFN-Υ production for test chemicals. We also examined the change of cell surface proteins on LNCs after sensitization by flow cytometry for some cell adhesion molecules(ICAM-1, E-cadherine, B7 molecule), T cell markers(CD3, CD4, CD8, T$\alpha$$\beta$,T${\gamma}$$\delta$) and B cell markers(LR1, CD45R, I-Ad). The number of ICAM-1 positive cells and B cells in LNCs were increased after sensitization with DNCB, TNCB, isoeugenol and 25%, 50% cinnamic aldehyde compared with that of vehicle as a control. In conclusion, the in vivo LLNA could provide more sensitive screening test for moderate to strong sensitizers and some weak sensitizers including cosmetic raw materials than the in vitro LLNA. The production of IFN-Υ by allergen-activated LNCs might be a values indicators without radioisotopes for the identification of contact allergens. Detection of allergens by testing the increase of ICAM-1 positive cells and B cells in LNCs by flow cytometry might be used as a test method to detect allergens.

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Development of a Machine-Learning Predictive Model for First-Grade Children at Risk for ADHD (머신러닝 분석을 활용한 초등학교 1학년 ADHD 위험군 아동 종단 예측모형 개발)

  • Lee, Dongmee;Jang, Hye In;Kim, Ho Jung;Bae, Jin;Park, Ju Hee
    • Korean Journal of Childcare and Education
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    • v.17 no.5
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    • pp.83-103
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    • 2021
  • Objective: This study aimed to develop a longitudinal predictive model that identifies first-grade children who are at risk for ADHD and to investigate the factors that predict the probability of belonging to the at-risk group for ADHD by using machine learning. Methods: The data of 1,445 first-grade children from the 1st, 3rd, 6th, 7th, and 8th waves of the Korean Children's Panel were analyzed. The output factors were the at-risk and non-risk group for ADHD divided by the CBCL DSM-ADHD scale. Prenatal as well as developmental factors during infancy and early childhood were used as input factors. Results: The model that best classifies the at-risk and the non-risk group for ADHD was the LASSO model. The input factors which increased the probability of being in the at-risk group for ADHD were temperament of negative emotionality, communication abilities, gross motor skills, social competences, and academic readiness. Conclusion/Implications: The outcomes indicate that children who showed specific risk indicators during infancy and early childhood are likely to be classified as being at risk for ADHD when entering elementary schools. The results may enable parents and clinicians to identify children with ADHD early by observing early signs and thus provide interventions as early as possible.

Prediction of Coagulation/Flocculation Treatment Efficiency of Dissolved Organic Matter (DOM) Using Multiple DOM Characteristics (다중 유기물 특성 지표를 활용한 용존 유기물질 응집/침전 제거효율 예측)

  • Bo Young Kim;Ka-Young Jung;Jin Hur
    • Journal of Korean Society on Water Environment
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    • v.39 no.6
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    • pp.465-474
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    • 2023
  • The chemical composition and molecular weight characteristics of dissolved organic matter (DOM) exert a profound influence on the efficiency of organic matter removal in water treatment systems, acting as efficiency predictive indicators. This research evaluated the primary chemical and molecular weight properties of DOM derived from diverse sources, including rivers, lakes, and biomasses, and assessed their relationship with the efficiency of coagulation/flocculation treatments. Dissolved organic carbon (DOC) removal efficiency through coagulation/flocculation exhibited significant correlations with DOM's hydrophobic distribution, the ratio of humic-like to protein-like fluorescence, and the molecular weight associated with humic substances (HS). These findings suggest that the DOC removal rate in coagulation/flocculation processes is enhanced by a higher presence of HS in DOM, an increased influence of externally sourced DOM, and more presence of high molecular weight compounds. The results of this study further posit that the efficacy of water treatment processes can be more accurately predicted when considering multiple DOM characteristics rather than relying on a singular trait. Based on major results from this study, a predictive model for DOC removal efficiency by coagulation/flocculation was formulated as: 24.3 - 7.83 × (fluorescence index) + 0.089 × (hydrophilic distribution) + 0.102 × (HS molecular weight). This proposed model, coupled with supplementary monitoring of influent organic matter, has the potential to enhance the design and predictive accuracy for coagulation/flocculation treatments targeting DOC removal in future applications.

Prevalence Rates of Risk Factors of Metabolic Syndrome, and Its Related with Obesity Indices Among the Health Checkup Examinees (건강검진 수검자들의 대사증후군 위험인자별 유병률 및 비만지표와의 관련성)

  • Park, Kyu-Ri;Cho, Young-Chae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.3
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    • pp.153-162
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    • 2016
  • The aim of this study was to estimate the prevalence of the metabolic syndrome risk factors for adults in the general population, understand the relationship of each factor with the obesity indicators, and examine the relevance and validity for predicting the metabolic syndrome in obese indicators. The study subjects were 1,051 adults aged 20 years and over, who underwent a health package check-up at the Korea Association of Health Promotion, D-branch from Feb. to Nov. 2014. As a result, the prevalence rates of metabolic syndrome of the study subjects were 21.5%, and the prevalence rates of the metabolic risk factors were as follows: 31.8% of men and 41.6% of women for abdominal obesity; 35.6% of men and 17.3% of women for TG; 17.6% of men and 34.2% of women for HDL-C; 53.5% of men and 35.9% of women for blood pressure; and 14.9% of men and 6.8% of women for FBS. The prevalence rates of metabolic syndrome were significantly higher in the older age group, in the group with the higher BMI, and in the group of higher level of drinking frequency. In the predictive indicators of obesity on metabolic syndrome risk factors, the waist / height ratio was higher than other indicators. Conclusively, WHtR appeared to be a useful indicator to show abdominal obesity and is better in selecting metabolic syndrome patients compared to other obesity indicators.

Comparison of the Usefulness of Lipid Ratio Indicators for Prediction of Metabolic Syndrome in the Elderly Aged 65 Years or Older (65세 이상 고령자에서 대사증후군 예측을 위한 지질비율 지표의 유용성 비교)

  • Shin, Kyung-A;Kim, Eun Jae
    • Journal of the Korea Convergence Society
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    • v.13 no.1
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    • pp.399-408
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    • 2022
  • The purpose of this study was to compare the usefulness of the lipid ratio indicators for the diagnosis of metabolic syndrome in the elderly aged 65 years or older. From January 2018 to December 2020, 1,464 people aged 65 years or older who underwent a health checkup at a general hospital in Seoul were included. Lipid ratio indicators were measured through blood tests. The prevalence of metabolic syndrome according to the quartiles of the lipid ratio index was confirmed by logistic regression analysis. In addition, the metabolic syndrome predictive ability and cutoff value of the lipid ratio indices were estimated with the receiver operating characteristic(ROC) curve. The correlation between atherogenic index of plasma(AIP) and waist circumference was the highest in both men and women(r=0.278, p<0.001 vs r=0.252, p<0.001). As for the lipid ratio indices, the incidence of metabolic syndrome was higher in the fourth quartile than in the first quartile. The area under the ROC curve(AUC) value of AIP was higher at 0.826(95% CI=0.799-0.850) and 0.852(95% CI=0.820-0.881) for men and women, respectively, compared to other lipid ratio indicators, and the optimal cutoff values for both men and women was 0.44(p<0.001). Therefore, the AIP among the lipid ratio indicators was found to be the most useful index for diagnosing metabolic syndrome in the elderly aged 65 years or older.

A Time Series-Based Statistical Approach for Trade Turnover Forecasting and Assessing: Evidence from China and Russia

  • DING, Xiao Wei
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.4
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    • pp.83-92
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    • 2022
  • Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.

Forecasting Government Bond Yields in Thailand: A Bayesian VAR Approach

  • BUABAN, Wantana;SETHAPRAMOTE, Yuthana
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.3
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    • pp.181-193
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    • 2022
  • This paper seeks to investigate major macroeconomic factors and bond yield interactions in Thai bond markets, with the goal of forecasting future bond yields. This study examines the best predictive yields for future bond yields at different maturities of 1-, 3-, 5-, 7-, and 10-years using time series data of economic indicators covering the period from 1998 to 2020. The empirical findings support the hypothesis that macroeconomic factors influence bond yield fluctuations. In terms of forecasting future bond yields, static predictions reveal that in most cases, the BVAR model offers the best predictivity of bond rates at various maturities. Furthermore, the BVAR model has the best performance in dynamic rolling-window, forecasting bond yields with various maturities for 2-, 4-, and 8-quarters. The findings of this study imply that the BVAR model forecasts future yields more accurately and consistently than other competitive models. Our research could help policymakers and investors predict bond yield changes, which could be important in macroeconomic policy development.

Analysis of Suicide Research on Multicultural Youth in Korea

  • Oh, Youngsub
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.5
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    • pp.269-277
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    • 2018
  • As multicultural population has been drastically increasing over the decade in Korea, their quality of life needs to be studied. This study focuses on multicultural youths' suicidal issue in Korea. Suicide is one of the most obvious indicators to show the current status of mental health. Unfortunately, suicide attempt rate of multicultural youths was two-times more than that of non-multicultural youths in Korea during the past two years(2014-15). Through the literature review in Korea as well as the United States, this study explores the related variables to their suicide attempt. Research result says that multicultural youth's suicide is related to a variety of variables, including physical, psychological, educational, socio-economical, and cultural variables. Research implications are as follows: First, these variables can be utilized as predictive or protective factors to prevent their suicide. Second, theoretical framework for comprehensively understanding their suicidal issues needs to be developed. Third, both emergent and normal suicidal interventions need to be provided for multicultural youth in Korea.

Breast Cancer Screening in Morocco: Performance Indicators During Two Years of an Organized Programme

  • Fakir, Samira El;Najdi, Adil;Khazraji, Youssef Chami;Bennani, Maria;Belakhel, Latifa;Abousselham, Loubna;Lyoussi, Badiaa;Bekkali, Rachid;Nejjari, Chakib
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.15
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    • pp.6285-6288
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    • 2015
  • Background: Breast cancer is commonly diagnosed at late stages in countries with limited resources. In Morocco, breast cancer is ranked the first female cancer (36.1%) and screening methods could reduce the proportion presenting with a late diagnosis. Morocco is currently adopting a breast cancer screening program based on clinical examination at primary health facilities, diagnosis at secondary level and treatment at tertiary level. So far, there is no systematic information on the performance of the screening program for breast cancer in Morocco. The aim of this study was to analyze early performance indicators. Materials and Methods: A retrospective evaluative study conducted in Temara city. The target population was the entire female population aged between 45-70 years. The study was based on process and performance indicators collected at the individual level from the various health structures in Tamara between 2009 and 2011. Results: A total of 2,350 women participated in the screening program; the participation rate was 35.7%. Of these, 76.8% (1,806) were married and 5.2% (106) of this group had a family history of breast cancer. Of the women who attended screening, 9.3% (190) were found to have an abnormal physical examination findings. A total of 260 (12.7%) were referred for a specialist consultation. The positive predictive value of clinical breast examination versus mammography was 23.0%. Forty four (35.5%) of the lesions found on the mammograms were classified as BI-RADs 3; 4 or 5 category. Cancer was found in 4 (1.95%) of the total number of screened women and benign cases represented 0.58%. Conclusions: These first results of the programme are very encouraging, but there is a need to closely monitor performance and to improve programme procedures with the aim of increasing both the participation rate and the proportion of women eligible to attend screening.